Junior AI Engineer

Join Soothsayer Analytics in Hyderabad as a Junior AI Engineer and launch your career in Artificial Intelligence. This full-time role offers a unique opportunity to work on cutting-edge Generative AI (GenAI), Machine Learning (ML), and data-driven projects across various industries. We are looking for a motivated individual with a minimum of 2 years of hands-on experience, or strong internship/project background, in machine learning, NLP, or GenAI. You will play a key role in supporting the development and deployment of AI models, contributing to robust data preparation pipelines, and gaining valuable insights into best practices in MLOps and applied AI engineering.

About The Role

Soothsayer Analytics, a global AI & Data Science consultancy with a strong presence in Hyderabad, is seeking a Junior AI Engineer. This position is ideal for aspiring AI professionals eager to contribute to innovative ML and GenAI solutions for enterprise clients.

Job Overview

We are hiring a Junior AI Engineer with at least 2 years of practical experience (or substantial internships/projects) in machine learning, NLP, or GenAI. The role involves supporting the entire lifecycle of AI models, from data processing to deployment, under the guidance of experienced professionals.

Key Responsibilities

Model Development & Support

• Assist in the development of various ML models, including classification, regression, clustering, and forecasting techniques.
• Contribute to the fine-tuning of Large Language Models (LLMs) and prompt engineering for advanced AI applications (e.g., GPT, LLaMA).
• Experiment with and implement vector databases and Retrieval Augmented Generation (RAG) pipelines for GenAI solutions.

Data Preparation & Engineering

• Work with both structured and unstructured datasets to prepare them for ML model training.
• Perform essential data cleaning, feature engineering, and contribute to the development of basic data processing pipelines.

MLOps & Deployment (Learning Role)

• Support the containerization and deployment of machine learning models using tools like Docker and Kubernetes.
• Gain practical experience in implementing Continuous Integration and Continuous Deployment (CI/CD) pipelines for ML workflows.

Collaboration & Learning

• Collaborate closely with senior engineers and data scientists, receiving mentorship and guidance.
• Document research experiments, development processes, and present findings to both technical and business stakeholders.

Required Skills & Qualifications

Education

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related field.

Experience

Minimum of 1 year of experience, including relevant internships, academic projects, or full-time roles.

Technical Skills

• Programming: Proficient in Python, with experience in libraries such as pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.
• ML Basics: Solid understanding of fundamental ML concepts including regression, classification, clustering, and time-series analysis.
• GenAI/LLMs: Familiarity with prompt engineering, basics of LangChain, and core concepts of RAG.
• Databases: Experience with SQL; exposure to NoSQL and vector databases (e.g., Pinecone, FAISS) is beneficial.
• MLOps Exposure: Foundational knowledge of Docker, Git, and basic CI/CD principles.

Bonus Skills

Knowledge of vision models, transformer architectures, or experience with cloud AI services like AWS SageMaker, Azure ML, or GCP Vertex AI.

Instructions For Candidates

• Submit a detailed resume that highlights your academic and industry projects in Machine Learning and AI.
• Complete the provided skills matrix with accurate details and self-ratings for each skill.